lecture18 - Motion Estimation Why estimate motion? Lots of...

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Motion Estimation
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Why estimate motion? Lots of uses Motion Detection Track object behavior Correct for camera jitter (stabilization) Align images (mosaics) 3D shape reconstruction Video Compression
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Optical flow Measurement of motion at every pixel
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Optical flow An image from Hamburg Taxi Sequence
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Video Mosaics
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Video Mosaics
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Video Mosaics
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Video Compression
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Geo Registration
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Video Segmentation
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Structure From Motion
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Optical flow Measurement of motion at every pixel
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Problem definition: optical flow How to estimate pixel motion from image H to image I? Solve pixel correspondence problem given a pixel in H, look for nearby pixels of the same color in I Key assumptions color constancy : a point in H looks the same in I – For grayscale images, this is brightness constancy small motion : points do not move very far This is called the optical flow problem
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Optical flow constraints (grayscale images) Let’s look at these constraints more closely brightness constancy: Q: what’s the equation? small motion: (u and v are less than 1 pixel) suppose we take the Taylor series expansion of I:
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Optical flow equation Combining these two equations In the limit as u and v go to zero, this becomes exact
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Optical flow equation Q: how many unknowns and equations per pixel?
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This note was uploaded on 06/12/2011 for the course CAP 5415 taught by Professor Staff during the Fall '08 term at University of Central Florida.

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lecture18 - Motion Estimation Why estimate motion? Lots of...

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